PropertyValue
?:abstract
  • ABSTRACT Objective: To determine the diagnostic accuracy of Magnetic Resonance Imaging in patients with suspicion of central nervous system infections keeping cerebrospinal fluid(lumbar puncture) findings as gold standard Study Design: Validity study Place and Duration of Study: Department of Radiology, Pakistan Institute of Medical Sciences Hospital, Islamabad, from Oct 2017 to Jul 2018 Methodology: A total of 275 patients suspected for central nervous system infection of age 1 day-18 years presenting in children OPD and main OPD of PIMS hospital, of either gender were included Patients with congenital anomalies e g Dandy Walker Malformations, Chiari Malformations, Anencephaly, Neural Tube defects and brain tumor were excluded All the patients then underwent MRI and lumbar puncture as a routine protocol Presence of central nervous system infections was checked in both Data was analyzed using SPSS version 16 0 Results: In magnetic resonance imaging positive patients, 160(90 4%) were True Positive and 17(9 6%) were False Positive Among 98 Magnetic Resonance Imaging negative patients, 13(13 3%) were False Negative whereas 85(86 7%) were True Negative Sensitivity of magnetic resonance imaging in the patients with suspicion of central nervous system infections keeping cerebrospinal fluid(lumbar puncture) findings as gold standard was found to be 92 49%, specificity 83 33%, positive predictive value 90 40%, negative predictive value 86 73% an d diagnostic accuracy of 89 09% Conclusion: Diagnostic accuracy of MRI for diagnosing central nervous system infections is quite high The primary imaging modality in central nervous system infections is magnetic resonance imaging
is ?:annotates of
?:creator
?:journal
  • Pakistan_Armed_Forces_Medical_Journal
?:license
  • unk
?:publication_isRelatedTo_Disease
is ?:relation_isRelatedTo_publication of
?:source
  • WHO
?:title
  • Accuracy of Magnetic Resonance Imaging in the Diagnosis of Central Nervous System Infections in Children and Adolescents
?:type
?:who_covidence_id
  • #831300
?:year
  • 2020

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